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High Memory Usage on Jetson TX2 #72
Description
Hello,
I just gave a try on your project. I've been trying to set up the environment for a couple of days. And finally could run it with a little bit changes in the mention configuration on your repo. My configuration is as following:
Jetson TX2:
- Jetpack 3.3 (L47 28.2.1)
- Opencv 3.4.1 with the contrib modules
- Tensorflow 1.9 with gpu
My target was to set up opencv 3.4.1 and Tensorflow 1.6. But there were hundreds of error while installing Tensorflow! It's a just a simple pip installation process, but it took a lot of sweat.
Now, I got an average of 20 FPS which is absolutely breathtaking at this moment. Yet there is a problem, a huge problem I would say. While running the camera stream and video file, memory usage is about 7 Gb with/without visualization which is hard to accept! I was wondering if it's caused by the version of tensorflow. What was your memory usage? Can it be implemented in caffe or pytorch? I would say it's the best performer till now with a huge resource. How do I optimize it as I will be running a whole lot other programs with the detector? Thanks
Activity
naisy commentedon Jul 7, 2019
Hi @magiccreator69,
Unfortunately, the ARM version of Tensorflow requires a large amount of memory resources when loading the CUDA library.
This problem can not be solved.
For both speed and memory resources, TensorRT/C ++ will be the best answer.
root1369 commentedon Jul 8, 2019
Thanks for a prompt response.
You meant should optimize the models using TensorRT, right? Like mentioned here? https://github.com/NVIDIA-AI-IOT/tf_trt_models
That way less memory resource is used? No harm in trying though. I'll give it a try and keep you posted.
naisy commentedon Jul 8, 2019
Hi @magiccreator69,
No. TF-TRT is python. That uses tensorflow.
You can try https://github.com/Ghustwb/MobileNet-SSD-TensorRT
TensorRT/C++ is really different from TF-TRT.
root1369 commentedon Jul 8, 2019
well. in that case, I don't need to install tensorflow, right? just opencv and cuda libraries are fine? If I don't need to use tensorflow for this, do I need to use any other framework?
naisy commentedon Jul 8, 2019
Hi @magiccreator69,
Yes, you don't need tensorflow. The framework is TensorRT. It is included in JetPack 3.3.
https://developer.nvidia.com/embedded/jetpack-3_3